Computer Vision Software Engineer, Senior

Job Number: R0242681

The Opportunity: As a Senior Computer Vision Engineer, you will design, develop, and optimize advanced computer vision and multisensor fusion algorithms supporting GEOINT mission workflows. You will lead the development of deep learning models, realtime tracking systems, and GPU accelerated pipelines deployed in operational environments. You will shape next generation tools that integrate imaging physics, ML-based behavior inference, and multisensor fusion.

You’ll join a collaborative technical delivery team where you’ll contribute to secure, reliable, usercentric tools that accelerate mission outcomes.

• Develop and implement deep learning computer vision models, with a focus on sensor fusion and target tracking
• Collaborate with multidisciplinary teams to design, develop, test, and deploy technical solutions in Python or C++
• Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision applications
• Contribute to the architecture and implementation of novel single and multi-sensor detection and tracking and fusion of targets

• 6+ years of experience developing computer vision algorithms for detection, tracking, or multisensor fusion in remote sensing or GEOINT relevant environments
• 2+ years of experience applying deep learning to computer vision problems using transformer-based or self-supervised architectures
• Experience implementing model pipelines in Python or C++, including training, evaluation, and deployment workflows
• Knowledge of GPU accelerated development using CUDA, RAPIDS, or GPU programming frameworks
• Experience with administration of continuous integration/continuous deployment (CI/CD) pipelines using Kubernetes, Docker, or Jenkins
• Experience with Agile methodology, extreme programming, software engineering, product management, and with acquiring client requirements and resolving workflow problems through automation optimization
• Knowledge of classical tracking or estimation methods, such as Kalman or extended filters, to support realtime algorithm development
• Ability to design, test, and optimize algorithms for operational performance in constrained computing environments such as multiGPU servers or cloud
• TS/SCI clearance
• Bachelor’s degree in a STEM field

• Experience with GPU accelerated deep learning, including CUDA kernel development, TensorRT optimization, RAPIDS, or distributed multiGPU training
• Experience developing synthetic data, kinematic target models, or scenario simulation tools to support algorithm training or evaluation
• Experience with advanced estimation, tracking, and fusion techniques such as joint multisensor registration, Bayesian fusion, particle filters, or deep multiobject tracking pipelines
• Knowledge of geospatial data formats, sensor phenomenology, or remote sensing exploitation workflows
• Experience with MLOps or scalable deployment systems, including Docker, Kubernetes, ONNX Runtime, Triton Inference Server, or similar
• Experience building or optimizing microservice architectures or distributed systems for realtime data processing
• Experience integrating CV models into edge, embedded, or latency‑constrained operational environments
• Experience with transformer‑based vision architectures beyond DINO/CLIP/SAM such as ViT variants or self‑supervised multimodal encoders
• Experience with cloud ML platforms such as AWS Gov Cloud, Azure ML, or on‑premises GPU clusters
• Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, AI/ML, Physics, Mathematics or other related field preferred;
  Doctorate degree in Computer Science, Electrical Engineering, Computer Engineering, AI/ML, Physics, Mathematics or other related field a plus

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required.

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